Parking Space

Parking space management is a growing research area focused on improving parking efficiency and reducing urban congestion through automated detection and optimization. Current research emphasizes computer vision techniques, employing convolutional neural networks, transformer-based architectures, and object detection algorithms (like YOLO) to identify occupied and vacant spaces from camera images, often incorporating multi-camera systems and fisheye lenses for comprehensive views. These advancements leverage techniques like imitation learning and crowdsensing to enhance accuracy and reduce reliance on manual labeling, leading to more efficient and cost-effective smart parking systems. The ultimate goal is to create real-time, accurate parking space information for drivers and urban planners, thereby mitigating traffic congestion and improving urban mobility.